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Reflections on the Development of Spatially Explicit Methods for GeoAI
Topics: Geographic Information Science and Systems
, Spatial Analysis & Modeling
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Keywords: GeoAI, Deep Learning Session Type: Virtual Paper Abstract Day: Tuesday Session Start / End Time: 3/1/2022 11:20 AM (Eastern Time (US & Canada)) - 3/1/2022 12:40 PM (Eastern Time (US & Canada)) Room: Virtual 21
Authors:
Song Gao, University of Wisconsin-Madison
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Abstract
The technological progress in the field of artificial intelligence has brought new opportunities and challenges to the intelligent development and innovative research in geography and geosciences. Geospatial artificial intelligence (GeoAI) refers to the interdisciplinary research direction that combines geography, earth science and artificial intelligence, and seeks to solve major scientific and engineering problems in human-environmental interaction systems through the research and development of spatial intelligence in machines to improve the dynamic perception, intelligent reasoning and knowledge discovery of geographic phenomena and earth science processes. This presentation will briefly summarize the roots of GeoAI development, introduce spatially explicit AI models, and review recent GeoAI research and applications.
Reflections on the Development of Spatially Explicit Methods for GeoAI
